18.2 Regular Expressions
The rebus package is a good resource for building regular expressions.
## Warning: package 'rebus' was built under R version 4.0.2##
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## alphaThe %R% operator concatenates the regular expression. START represents regex “^” meaning “starting with”. END represents regex “$” meaning “ending with”.
x <- austen_books() %>%
filter(book == "Sense & Sensibility") %>%
select(text) %>%
head(100) %>%
pull()Here are lines from Sense & Sensibility that start with “Mr”.
## [1] "Mrs. Henry Dashwood to his wishes, which proceeded not merely from"
## [2] "Mr. Dashwood's disappointment was, at first, severe; but his temper was"
## [3] "Mr. John Dashwood had not the strong feelings of the rest of the"ANY_CHAR represents regex “.” Here are lines from Sense & Sensibility with pattern “handsome”
## [1] "them three thousand pounds: it would be liberal and handsome! It would"char_class() is similar to ANY_CHAR except that it matches any character from the string parameter. It is the same as regex “[]”. The opposite is negated_char_class(), which is the same as “[^]”. char_class() can accept ranges, such as “0-9”, and “a-z”. DGT is the same thing as “0-9”.
## [1] "apple" "Aardvark"DOT, CARAT, and DOLLAR represent special characters, “.”, “%”, and “$”. Function or() provides alteration.
## [,1]
## [1,] "cat"
## [2,] "dog"Look for repeating patterns with optional(), zero_or_more(), one_or_more(), and repeated().
Wrap a rebus expression in capture() to create a column in the output for the match to each captured part of the regex.
phone_string <- c("555-123-4567",
"(555)123-4567",
"555.123.4567",
"555-123-4567 (M), 555-123-7654 (H)")
phone_pattern <-
capture(DGT %R% DGT %R% DGT) %R% zero_or_more(char_class("()-.")) %R%
capture(DGT %R% DGT %R% DGT) %R% zero_or_more(char_class("()-.")) %R%
capture(DGT %R% DGT %R% DGT %R% DGT)
# first match with str_match()
phone_match <- str_match(phone_string, pattern = phone_pattern)
str_c("(", phone_match[, 2], ")", phone_match[, 3], "-", phone_match[, 4])## [1] "(555)123-4567" "(555)123-4567" "(555)123-4567" "(555)123-4567"# all matches with str_match_all() and lapply()
phone_match_all <- str_match_all(phone_string, pattern = phone_pattern)
lapply(phone_match_all, function(x){str_c("(", x[, 2], ")", x[, 3], "-", x[, 4])}) %>% unlist()## [1] "(555)123-4567" "(555)123-4567" "(555)123-4567" "(555)123-4567"
## [5] "(555)123-7654"You can refer to captured patterns with REF[0-9].
## [,1] [,2]
## [1,] "ll" "l"
## [2,] "ee" "e"
## [3,] "tt" "t"Here is an exercise working with the Oscal Wilde play “The Importance of Being Earnest”.
earnest <- read_lines("http://s3.amazonaws.com/assets.datacamp.com/production/course_2922/datasets/importance-of-being-earnest.txt")The text is between the lines with “START OF THE PROJECT” and “END OF THE PROJECT”. str_which() returns the indices where the string contains the pattern. The text consists of an introduction and the play itself. The play starts at “FIRST ACT”.
start <- str_which(earnest, fixed("START OF THE PROJECT"))
end <- str_which(earnest, fixed("END OF THE PROJECT"))
earnest_sub <- earnest[(start+1):(end-1)]
play_start <- str_which(earnest_sub, "FIRST ACT")
intro_line_index <- 1:(play_start - 1)
intro_text <- earnest_sub[intro_line_index]
play_text <- earnest_sub[-intro_line_index]
# remove the emptly lines
play_lines <- play_text[str_length(play_text) > 0] %>% as.character()
# print first 20 lines
writeLines(play_lines[1:20])## FIRST ACT
## SCENE
## Morning-room in Algernon's flat in Half-Moon Street. The room is
## luxuriously and artistically furnished. The sound of a piano is heard in
## the adjoining room.
## [Lane is arranging afternoon tea on the table, and after the music has
## ceased, Algernon enters.]
## Algernon. Did you hear what I was playing, Lane?
## Lane. I didn't think it polite to listen, sir.
## Algernon. I'm sorry for that, for your sake. I don't play
## accurately--any one can play accurately--but I play with wonderful
## expression. As far as the piano is concerned, sentiment is my forte. I
## keep science for Life.
## Lane. Yes, sir.
## Algernon. And, speaking of the science of Life, have you got the
## cucumber sandwiches cut for Lady Bracknell?
## Lane. Yes, sir. [Hands them on a salver.]
## Algernon. [Inspects them, takes two, and sits down on the sofa.] Oh! . . .
## by the way, Lane, I see from your book that on Thursday night, when
## Lord Shoreman and Mr. Worthing were dining with me, eight bottles ofHow would you identify lines where the character is starting to speak? You might look for a capitalized word followed by a “.”.
pattern <- START %R% ascii_upper() %R% one_or_more(WRD) %R% DOT
lines <- str_subset(play_lines, pattern)
# Extract the matching string (the character speaking)
who <- str_extract(lines, pattern)
# Let's see what we have
unique(who)## [1] "Algernon." "Lane." "Jack." "Cecily." "Ernest."
## [6] "University." "Gwendolen." "July." "Chasuble." "Merriman."
## [11] "Sunday." "Mr." "London." "Cardew." "Opera."
## [16] "Markby." "Oxonian."Close, but not perfect. If you know the characters, just search for them directly. or1() is like or() but lets you supply a vector of strings.
characters <- c("Algernon", "Jack", "Lane", "Cecily", "Gwendolen", "Chasuble",
"Merriman", "Lady Bracknell", "Miss Prism")
pattern <- START %R% or1(characters) %R% DOT
lines <- str_subset(play_lines, pattern)
# Extract the matching string (the character speaking)
who <- str_extract(lines, pattern)
# Let's see what we have
unique(who)## [1] "Algernon." "Lane." "Jack." "Cecily."
## [5] "Gwendolen." "Lady Bracknell." "Miss Prism." "Chasuble."
## [9] "Merriman."## who
## Algernon. Cecily. Chasuble. Gwendolen. Jack.
## 201 154 42 102 219
## Lady Bracknell. Lane. Merriman. Miss Prism.
## 84 21 17 41